Workshops

= Sample Size Calculation with GPower =
Introduction of the necessary concepts (power, effect size and type I/II errors), with small exercises to promote statistical reasoning. After a focus on the comparison of 2 independent groups, several extensions are highlighted. [webpage]

= Data Manipulation in R, tidyverse =
Introduction of the tidyverse packages dplyr and friends for intuitive and flexible data management in R. [webpage] [pdf]

= Visualization in R, tidyverse =
Introduction of the tidyverse package ggplot2 for intuitive and flexible visualization in R.  [webpage] [pdf]

Presentations

= R Primer =
Short introduction on the essentials of the R statistical programming tool. [webpage] [pdf]

= Data Representation =
Brief introduction to help structure data in preparation of statistical analyses; highlighting errors, inconveniences, common problems and solutions. [webpage] [pdf]

= Methodological & Statistical issues in research proposals =
Info session for experienced researchers to help highlight relevant aspects of the research aim and design that are part of a research proposal. [webpage] [pdf]

Technical Notes

= Corona hospitalisation SIR model =
Technical note on the analytical approximation of the popular SIR-equations which after reparametrization allow for straightforward parameter estimation and prediction of hospitalisation sustainability based on limited time series. Extensions that add flexibility are highlighted. [pdf] 
Please reference: Barbé, K.,  Blotwijk, S., & Cools, W. (2020) Data-driven epidemiological model to monitor the sustainability of hospital care, VUB Covid19 Technical Note No. ICDS043020.

Apps

interim analysis / error spending functions: simulator

GSDesigner

effect size calculator for 2-way & repeated measures ANOVA

shiny app
^{run locally with runGitHub('effectSizes','ICDS-VubUZ')}

didactical tool: effect size one-sided t-test

shiny app
^{run locally with runGitHub('shinyT','ICDS-VubUZ')}